UAV-based mangrove biomass estimation and carbon potential valuation in North Sumatra, Indonesia

Abstract

Mangrove forests are among the most carbon-dense coastal ecosystems, yet ongoing conversion to agriculture and oil palm plantations significantly reduces landscape-scale carbon storage and climate mitigation potential. This study quantified aboveground biomass (AGB) and carbon stocks across six land-use types within Karang Gading and Langkat Timur Laut Wildlife Reserve, North Sumatra, Indonesia, covering 928.42 ha. High-resolution unmanned aerial vehicle (UAV)–derived canopy height models were integrated with field-calibrated allometric equations, using basal area–weighted Lorey’s height to improve biomass estimation in structurally heterogeneous stands. Bias correction was applied to log-transformed models to minimize systematic error. Mean AGB ranged from 0.97 Mg ha⁻¹ in oil palm plantations to 278.54 Mg ha⁻¹ in natural mangroves. Corresponding aboveground carbon (AGC) stocks ranged from 0.46 to 130.92 Mg C ha⁻¹. Natural mangroves (92.82 ha) stored 12,151.99 Mg C (44,597.11 Mg CO₂e), while community forests (98 ha) stored 10,541.86 Mg C. In contrast, mixed agriculture and oil palm systems together contributed less than 2% of total landscape-level aboveground carbon. Under a conservative avoided deforestation scenario, total CO₂-equivalent stocks correspond to an indicative economic value of approximately USD 0.63–6.35 million at voluntary carbon market prices of USD 5–50 Mg CO₂e⁻¹. Although these values represent biophysical carbon stocks rather than verified emission reductions, the integration of UAV-derived structural metrics with field validation provides a robust and scalable framework for spatially explicit carbon accounting. These findings strengthen the empirical basis for evaluating land-use impacts on coastal carbon balance and support mitigation-oriented conservation and restoration planning in tropical mangrove landscapes.